Various types of biometric systems are used more and more in order to provide for increased security and/or enhanced user convenience. In particular, fingerprint sensing systems have been adopted in, for example, consumer electronic devices, thanks to their small form factor, high performance, and user acceptance.
Among the various available fingerprint sensing principles (such as capacitive, optical, thermal etc.), optical sensing is increasing interest.
The optical properties of a fingerprint sensing device may depend on external factors such as temperature. Moreover, the humidity is also important for an optical sensor, since it relates to the optical contact of the finger with the optical interface such as a display surface and determines image features like finger coverage and image contrast. In particular, low humidity may lead to an absence of moist between the finger and the sensor which can make a significant difference in image capture since dry fingers are more difficult for the optical sensor than sweaty fingers. Finger dryness can for example be affected by weather conditions and individual human factors.
In order to compensate for variations depending on external factors, parameters of the sensing device can be calibrated towards the current conditions. For example, a calibration is often performed at system startup and thereafter repeated with given time intervals.
However, continuous calibration at given time intervals may lead to an unnecessarily high power consumption when the fingerprint sensor is unused for long periods of time. The power consumption may be decreased by increasing the time between calibrations. However, this is an undesirable approach since increasing the time between calibrations may lead to situations where the sensing device is being used just prior to a scheduled calibration event, increasing the risk that the fingerprint sensor is not properly calibrated for the current operating conditions.